The Need for Accurate Risk Prediction Models for Road Mapping, Shared Decision Making and Care Planning for the Elderly with Advanced Chronic Kidney Disease

Pril (Makedon Akad Nauk Umet Odd Med Nauki). 2016 Nov 1;37(2-3):33-42. doi: 10.1515/prilozi-2016-0014.

Abstract

As people age, chronic kidney disease becomes more common, but it rarely leads to end-stage kidney disease. When it does, the choice between dialysis and conservative care can be daunting, as much depends on life expectancy and personal expectations of medical care. Shared decision making implies adequately informing patients about their options, and facilitating deliberation of the available information, such that decisions are tailored to the individual's values and preferences. Accurate estimations of one's risk of progression to end-stage kidney disease and death with or without dialysis are essential for shared decision making to be effective. Formal risk prediction models can help, provided they are externally validated, well-calibrated and discriminative; include unambiguous and measureable variables; and come with readily applicable equations or scores. Reliable, externally validated risk prediction models for progression of chronic kidney disease to end-stage kidney disease or mortality in frail elderly with or without chronic kidney disease are scant. Within this paper, we discuss a number of promising models, highlighting both the strengths and limitations physicians should understand for using them judiciously, and emphasize the need for external validation over new development for further advancing the field.

MeSH terms

  • Aged
  • Clinical Decision-Making*
  • Decision Making
  • Humans
  • Patient Care Planning*
  • Patient Participation
  • Renal Insufficiency, Chronic / therapy*
  • Risk Assessment